Albert Bow
Distributed Systems Engineer
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Location: London
Working model: On-site — 4+ days per week
Employment: Full-time
The Opportunity
What happens when your data grows 100x? This is an opportunity to join a high-growth AI company building the core infrastructure behind a data-intensive AI platform. The engineering team is responsible for the systems that store, index, query and process massive amounts of multimodal data — including video, images, 3D sensor data and documents. This is a role for engineers who enjoy solving difficult problems around scale, performance, reliability and distributed systems. You’ll have significant ownership, taking projects from architecture and design through to implementation, deployment, monitoring and optimisation.
What You'll Be Working On
- Designing and building distributed systems at scale
- Developing high-performance data infrastructure
- Building storage, indexing and querying systems
- Designing performant APIs and protocols
- Working with databases, caching, queues and replication
- Solving problems around scalability, consistency and reliability
- Identifying and resolving performance bottlenecks
- Making architectural decisions for systems designed to scale significantly
- Improving engineering standards through code reviews, testing and knowledge sharing
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What We're Looking For
- Strong production experience with Python or TypeScript
- Strong experience with Go, Rust, C++, Java or another statically typed language
- Proven experience building and owning distributed systems in production
- Strong understanding of:
- Databases
- Partitioning
- Replication
- Queuing
- Caching
- Consistency
- Excellent knowledge of data structures, algorithms and core CS fundamentals
- Experience taking systems through design, development, deployment, monitoring and optimisation
- Strong understanding of system performance and failure modes
- Comfortable working autonomously on ambiguous and technically complex problems
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The Ideal Background
You could come from a range of technically demanding environments, including:
- Distributed systems
- Data infrastructure
- Database engineering
- Storage systems
- Search and indexing
- High-throughput platforms
- Trading or financial infrastructure
- Cloud infrastructure
- Large-scale backend systems
- Performance-critical software
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